Literature DB >> 12707145

Determining the number of beds in the postanesthesia care unit: a computer simulation flow approach.

Eric Marcon1, Saïd Kharraja, Nicole Smolski, Brigitte Luquet, Jean Paul Viale.   

Abstract

UNLABELLED: Designing a new operating room (OR) suite is a difficult process owing to the number of caregivers involved and because decision-making managers try to minimize the direct and indirect costs of operating the OR suite. In this study, we devised a computer simulation flow model to calculate, first, the minimum number of beds required in the postanesthesia care unit (PACU). In a second step, we evaluated the relationship between the global performance of the OR suite in terms of OR scheduling and number of staffed PACU beds and porters. We designed a mathematical model of OR scheduling. We then developed a computer simulation flow model of the OR suite. Both models were connected; the first one performed the input flows, and the second simulated the OR suite running. The simulations performed examined the number of beds in the PACU in an ideal situation or in the case of reduction in the number of porters. We then analyzed the variation of number of beds occupied per hour in the PACU when the time spent by patients in the PACU or the number of porters varied. The results highlighted the strong impact of the number of porters on the OR suite performance and particularly on PACU performances. IMPLICATIONS: Designing new operating room (OR) facilities implies many decisions on the number of ORs, postanesthesia care unit (PACU) beds, and on the staff of nurses and porters. To make these decisions, managers can use rules of thumb or recommendations. Our study highlights the interest of using flow simulation to validate these choices. In this case study we determine the number of PACU beds and porter staff and assess the impact of decreasing the number of porters on PACU bed requirements.

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Year:  2003        PMID: 12707145     DOI: 10.1213/01.ane.0000056701.08350.b9

Source DB:  PubMed          Journal:  Anesth Analg        ISSN: 0003-2999            Impact factor:   5.108


  11 in total

1.  Impact of surgical sequencing on post anesthesia care unit staffing.

Authors:  Eric Marcon; Franklin Dexter
Journal:  Health Care Manag Sci       Date:  2006-02

Review 2.  [Key performance indicators of OR efficiency. Myths and evidence of key performance indicators in OR management].

Authors:  M Schuster; L L Wicha; M Fiege
Journal:  Anaesthesist       Date:  2007-03       Impact factor: 1.041

3.  [Utilization rates and turnover times as indicators of OR workflow efficiency].

Authors:  M Schuster; L L Wicha; M Fiege; A E Goetz
Journal:  Anaesthesist       Date:  2007-10       Impact factor: 1.041

4.  What is the best workflow for an operating room? A simulation study of five scenarios.

Authors:  Riitta A Marjamaa; Paulus M Torkki; Eero J Hirvensalo; Olli A Kirvelä
Journal:  Health Care Manag Sci       Date:  2009-06

5.  Scheduling elective surgeries: the tradeoff among bed capacity, waiting patients and operating room utilization using goal programming.

Authors:  Xiangyong Li; N Rafaliya; M Fazle Baki; Ben A Chaouch
Journal:  Health Care Manag Sci       Date:  2015-07-17

Review 6.  Systematic review of the use of computer simulation modeling of patient flow in surgical care.

Authors:  Boris G Sobolev; Victor Sanchez; Christos Vasilakis
Journal:  J Med Syst       Date:  2009-07-07       Impact factor: 4.460

7.  Modeling the impact of changing patient transportation systems on peri-operative process performance in a large hospital: insights from a computer simulation study.

Authors:  Danny Segev; Retsef Levi; Peter F Dunn; Warren S Sandberg
Journal:  Health Care Manag Sci       Date:  2012-02-14

8.  Systematic identification and management of barriers to vascular surgery patient discharge time of day.

Authors:  Gaurav Sharma; Danny Wong; Dean J Arnaoutakis; Samir K Shah; Alice O'Brien; Stanley W Ashley; C Keith Ozaki
Journal:  J Vasc Surg       Date:  2016-09-19       Impact factor: 4.268

9.  The Distributions of Weekday Discharge Times at Acute Care Hospitals in the State of Florida were Static from 2010 to 2018.

Authors:  Richard H Epstein; Franklin Dexter; Christian Diez
Journal:  J Med Syst       Date:  2020-01-03       Impact factor: 4.460

10.  Estimating the cost of no-shows and evaluating the effects of mitigation strategies.

Authors:  Bjorn P Berg; Michael Murr; David Chermak; Jonathan Woodall; Michael Pignone; Robert S Sandler; Brian T Denton
Journal:  Med Decis Making       Date:  2013-03-20       Impact factor: 2.583

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